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Modelling spatiotemporal variability of bed roughness and its role in the morphological development of tidal sand waves

Bottenberg, D.J.M. (2021) Modelling spatiotemporal variability of bed roughness and its role in the morphological development of tidal sand waves.

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Abstract:The sandy seabed of many coastal seas consists of a variety of rhythmic bed patterns. Among the largest are sand waves with dimensions that cover a significant portion of the water depth and have considerable migration rates. Coastal seas are generally busy areas to which sand waves could pose a serious threat. Morphological models can predict sand wave evolution and migration for many years in the future. To study the morphological behaviour of sand waves in tidal environments, processbased models are set-up. However, some physical processes, such as the bed roughness, remain simplified. It is often assumed uniform while observations show distinct variations in bed patterns over sand waves. Modelling these variations may lead to an increase in the accuracy of the process-based morphological models for long-term sand wave development. This study uses the 3D process-based morphological model Delft3D in the 2DV mode. The roughness predictor VRIJN07 and sediment transport model TR2004 is used to estimate dynamic bed roughness based on hydrodynamic conditions and sediment properties. The reference case consists of a uniform Chézy coefficient of 75 m0.5s -1 (C75) combined with sediment transport model TR1993. The aim is to understand how spatiotemporal variable bed roughness influences the hydro-morphodynamic processes that govern sand wave development and improve long term simulation results of the reference case. To achieve this, firstly a flat bed is used to focus on the temporal variability in bed roughness and its effect on hydro-morphodynamics. Fastest growing mode (FGM) simulations have been performed that estimate the bedform wavelength with the largest growth rate of a given parameter setup. This wavelength is therefore most likely to emerge on the long term. Secondly, by using FGM simulations the initial topography is extended to a low-amplitude 0.5-meter sand wave to introduce spatial variation to the bed roughness estimates. Thirdly, the amplitude is increased to 1.5- meters and spatial variability of bed roughness is forced by linearly interpolating a Chézy coefficient of 50 m0.5s -1 at the sand wave crest and 80 m0.5s -1 at the trough (Cspatial). Finally, long term simulations have been conducted for C75/TR1993, Cspatial/TR1993 and VRIJN07/TR2004. The results show that the bed roughness has a large influence on the strength of circulation cells, caused by decreasing flow velocities as flow passes over the sand wave. Generally, this gives rise to faster growth rates but shorter preferred wavelengths. VRIJN07 estimates larger bed roughness than C75 which is mainly caused by the contribution of megaripple roughness height and is highly dynamic temporally. This leads to VRIJN07 having larger sand wave growth rates than C75. However, the transport model greatly influences the sediment transport rates. TR1993 has transport rates several times larger than TR2004, meaning TR1993 combinations lead to fast growing short wavelength sand waves while TR2004 leads to very slow growth for large wavelengths. Furthermore, VRIJN07 estimates negligible spatial variation due to a mechanism limiting the maximum attainable megaripple roughness height being reached at all parts of the sand wave. This means that VRIJN07 is only temporally variable which limits the sand wave growth rate more by effectively reducing bed shear stress and sediment transport rates. Spatially averaged, Cspatial is rougher than C75 but smoother than VRIJN07. Linear interpolation of bed roughness causes local areas with increased erosion at the crest, while decreasing it at the trough. Long term, this limits the equilibrium height of sand waves to 6.2 meters. Compared to C75/TR1993 with 8.8 meters, this is a large improvement towards the average sand wave height in the North Sea that is between 2 meters for the smallest and >7 meters for the largest sand waves observed by Damen et al. (2018). VRIJN07/TR2004 severely overestimates these averages with approximately 13 meters and requires severely longer computation time. C75/TR1993 has proven itself to give simulation results with reasonable agreement to field observations by parameterizing complex near-bed processes. Using a constant Chézy coefficient also eliminates complex and elaborate feedback mechanisms, reducing uncertainty in the simulation results. Using VRIJN07/TR2004 for (spatio)temporal bed roughness modelling with the presented setup is not recommended. However, calibration could improve the results and increase the accuracy towards simulation results that match field conditions. Cspatial/TR1993 was introduced to force spatial variation in bed roughness and it provided a significant improvement of modelling equilibrium sand wave heights under North Sea conditions. This implies that bed roughness might have a larger influence on tidal sand waves than previously presumed. Also, modelling spatial variation rather than temporal variation has the effect on improving simulation results. Further research should focus on extending the model with an asymmetrical tide and wind-currents and -waves, VRIJN07 might translate these hydrodynamic processes to more accurate bed roughness which C75 and Cspatial are unable to do. Also, grain sorting and the influence of bio-organisms directly influence the bed roughness leading to spatial variability. Since modelling spatial variation in bed roughness was successful in increasing the accuracy, these processes could have a large effect.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Programme:Civil Engineering and Management MSc (60026)
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